A win-win for exhibitors and attendees? Tim describes using AI matchmaking at meetings as a win for both exhibitors and attendees.

I’m skeptical.

Let’s assume, for the moment, that the technology actually works. If so, I think suppliers will reap most of the touted benefits, quite possibly at the expense of attendees. Here’s why.

Successful matchmaking needs digital data about attendees. An AI platform cannot work without this information. Where will the data come from? Tim explains that a profile is built for each attendee, using sources like “LinkedIn, Google, and Facebook”, while also “scouring the web for additional information”.

Using social media platform information, even if attendee approval is requested first, creates a slippery slope, as privacy issues in meeting apps remain largely undiscussed and little considered by attendees during the rush of registration. The end result is that the AI matchmaking platform gains a rich reservoir of data about attendees that, without strong verifiable safeguards, may be sold to third parties or even given to suppliers.

In addition, let’s assume that exhibitors get great information about whom to target. The result: “high-value” attendees will be bombarded with even more meeting requests while attendees who don’t fit the platform’s predictions will be neglected.

In my opinion, the best and most likely to succeed third-party services for meetings are those that provide win-win outcomes for everyone concerned. Unfortunately it’s common (and often self-serving) to overlook a core question about meeting objectives —whom is your event for? — and end up with a “solution” that benefits one set of stakeholders over another.

How well will AI matchmaking work for attendees? Artificial intelligence is hot these days, so it’s inevitable that event companies talk about incorporating it into their products, if only because it’s a sure-fire way to get attention from the meetings industry.

I know something about AI, because in the ’80s I was a professor of computer science, and the thirty-year old theory of artificial neural networks — the heart of modern machine learning — were well established by then. AI had to wait, however, for the introduction of vastly more potent technology to allow practical implementation on today’s computers.

While the combination of powerful computing and well-established AI research is demonstrating incredible progress in areas such as real time natural language processing and translation, I don’t see why sucking social media and registration data into a database and using AI to look for correlations is going to provide attendee matchmaking that is superior to what can be achieved using participant-driven and participation-rich meeting process combined with attendees’ real-time event experience. (Once again, exhibitors may see a benefit by getting customized target attendee lists, but I’m looking for win-win here.)

As an attendee, when I enter a meeting room there’s a wealth of information available to me to help me make relevant connections. Friends introduce me to people I haven’t yet met, eavesdropping on conversations opens up more possibilities, body language and social groupings also provide important potential matchmaking information. None of these resources are included in an AI matchmaking database. All of them have led me (and just about everyone who’s ever attended meetings) to professional connections that matter.

“…it was one of the most innovative and eye-opening professional experiences I’ve had. Aside from coming back with lots of new tips and ideas, I easily established triple the number of new contacts, and formed stronger relationships with them, than at any other conference I’ve been to.”

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on Monday, August 7th, 2017 at 6:42 am and is filed under Event design.
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